Moderate Throughput Research Articles

Laser-assisted bioprinting of targeted cartilaginous spheroids for high density bottom-up tissue engineering

Multicellular spheroids such as microtissues and organoids have demonstrated great potential for tissue engineering applications in recent years as these 3D cellular units enable improved cell-cell and cell-matrix interactions. Current bioprinting processes that use multicellular spheroids as building blocks have demonstrated limited control on post printing distribution of cell spheroids or moderate throughput and printing efficiency. In this work, we presented a laser-assisted bioprinting approach able to transfer multicellular spheroids as building blocks for larger tissue structures. Cartilaginous multicellular spheroids formed by human periosteum derived cells (hPDCs) were successfully bioprinted possessing high viability and the capacity to undergo chondrogenic differentiation post printing. Smaller hPDC spheroids with diameters ranging from ∼100 to 150µm were successfully bioprinted through the use of laser-induced forward transfer method (LIFT) however larger spheroids constituted a challenge. For this reason a novel alternative approach was developed termed as laser induced propulsion of mesoscopic objects (LIPMO) whereby we were able to bioprint spheroids of up to 300µm. Moreover, we combined the bioprinting process with computer aided image analysis demonstrating the capacity to 'target and shoot', through automated selection, multiple large spheroids in a single sequence. By taking advantage of target and shoot system, multilayered constructs containing high density cell spheroids were fabricated.

Single-mitochondrion sequencing uncovers distinct mutational patterns and heteroplasmy landscape in mouse astrocytes and neurons

BackgroundMitochondrial (mt) heteroplasmy can cause adverse biological consequences when deleterious mtDNA mutations accumulate disrupting “normal” mt-driven processes and cellular functions. To investigate the heteroplasmy of such mtDNA changes, we developed a moderate throughput mt isolation procedure to quantify the mt single-nucleotide variant (SNV) landscape in individual mouse neurons and astrocytes. In this study, we amplified mt-genomes from 1645 single mitochondria isolated from mouse single astrocytes and neurons to (1) determine the distribution and proportion of mt-SNVs as well as mutation pattern in specific target regions across the mt-genome, (2) assess differences in mtDNA SNVs between neurons and astrocytes, and (3) study co-segregation of variants in the mouse mtDNA.Results(1) The data show that specific sites of the mt-genome are permissive to SNV presentation while others appear to be under stringent purifying selection. Nested hierarchical analysis at the levels of mitochondrion, cell, and mouse reveals distinct patterns of inter- and intra-cellular variation for mt-SNVs at different sites. (2) Further, differences in the SNV incidence were observed between mouse neurons and astrocytes for two mt-SNV 9027:G > A and 9419:C > T showing variation in the mutational propensity between these cell types. Purifying selection was observed in neurons as shown by the Ka/Ks statistic, suggesting that neurons are under stronger evolutionary constraint as compared to astrocytes. (3) Intriguingly, these data show strong linkage between the SNV sites at nucleotide positions 9027 and 9461.ConclusionsThis study suggests that segregation as well as clonal expansion of mt-SNVs is specific to individual genomic loci, which is important foundational data in understanding of heteroplasmy and disease thresholds for mutation of pathogenic variants.

Single-Mitochondrion Sequencing Uncovers Distinct Mutational Patterns and Heteroplasmy Landscape in Mouse Astrocytes and Neurons.

Mitochondrial (mt) heteroplasmy can cause adverse biological consequences when deleterious mtDNA mutations accumulate disrupting 'normal' mt-driven processes and cellular functions. To investigate the heteroplasmy of such mtDNA changes we developed a moderate throughput mt isolation procedure to quantify the mt single-nucleotide variant (SNV) landscape in individual mouse neurons and astrocytes In this study we amplified mt-genomes from 1,645 single mitochondria (mts) isolated from mouse single astrocytes and neurons to 1. determine the distribution and proportion of mt-SNVs as well as mutation pattern in specific target regions across the mt-genome, 2. assess differences in mtDNA SNVs between neurons and astrocytes, and 3. Study cosegregation of variants in the mouse mtDNA. 1. The data show that specific sites of the mt-genome are permissive to SNV presentation while others appear to be under stringent purifying selection. Nested hierarchical analysis at the levels of mitochondrion, cell, and mouse reveals distinct patterns of inter- and intra-cellular variation for mt-SNVs at different sites. 2. Further, differences in the SNV incidence were observed between mouse neurons and astrocytes for two mt-SNV 9027:G>A and 9419:C>T showing variation in the mutational propensity between these cell types. Purifying selection was observed in neurons as shown by the Ka/Ks statistic, suggesting that neurons are under stronger evolutionary constraint as compared to astrocytes. 3. Intriguingly, these data show strong linkage between the SNV sites at nucleotide positions 9027 and 9461. This study suggests that segregation as well as clonal expansion of mt-SNVs is specific to individual genomic loci, which is important foundational data in understanding of heteroplasmy and disease thresholds for mutation of pathogenic variants.

Blitzcrank: Fast Semantic Compression for In-Memory Online Transaction Processing

We present Blitzcrank, a high-speed semantic compressor designed for OLTP databases. Previous solutions are inadequate for compressing row-stores: they suffer from either low compression factor due to a coarse compression granularity or suboptimal performance due to the inefficiency in handling dynamic data sets. To solve these problems, we first propose novel semantic models that support fast inferences and dynamic value set for both discrete and continuous data types. We then introduce a new entropy encoding algorithm, called delayed coding, that achieves significant improvement in the decoding speed compared to modern arithmetic coding implementations. We evaluate Blitzcrank in both standalone microbenchmarks and a multicore in-memory row-store using the TPC-C benchmark. Our results show that Blitzcrank achieves a sub-microsecond latency for decompressing a random tuple while obtaining high compression factors. This leads to an 85% memory reduction in the TPC-C evaluation with a moderate (19%) throughput degradation. For data sets larger than the available physical memory, Blitzcrank help the database sustain a high throughput for more transactions before the I/O overhead dominates.

Temporal contrast enhancement of a Ti:Sapphire laser by nonlinear Fourier filtering

Temporal cleaning of high-power infrared (IR) pulses generated by a Ti:Sapphire system is demonstrated by the use of the Nonlinear Fourier Filtering (NFF) method. In a proof-of-principle experiment suppression of up to 1000 is achieved for the temporal pedestal prior to the main pulse, with a moderate (20-25%) overall throughput. This includes the same suppression ratio for the picosecond coherent pedestal in the direct vicinity of the main pulse. Based on the instantaneous, intensity-dependent and high-order switching characteristics of NFF, excellent pulse cleaning performance is observed. The efficient, high-contrast removal of the coherent pedestal from the foot of the main pulse even if its duration is shorter than 100 fs is compared with the capability of the plasma mirror technique. Calculations are also performed, supporting the experimentally observed sharp intensity dependence of the switching process, pointing out the dominant role of the ionization-based refractive index change.

Divergent pathogenetic outcomes in BALB/c mice following Omicron subvariant infection

Following the emergence of B.1.1.529 Omicron, the SARS-CoV-2 virus evolved into a significant number of sublineage variants that possessed numerous mutations throughout the genome, but particularly within the spike glycoprotein (S) gene. For example, the BQ.1.1 and the XBB.1 and XBB.1.5 subvariants contained 34 and 41 mutations in S, respectively. However, these variants elicited largely replication only or mild disease phenotypes in mice. To better model pathogenic outcomes and measure countermeasure performance, we developed mouse adapted versions (BQ.1.1 MA; XBB.1 MA; XBB.1.5 MA) that reflect more pathogenic acute phase pulmonary disease symptoms of SARS-CoV-2, as well as derivative strains expressing nano-luciferase (nLuc) in place of ORF7 (BQ.1.1 nLuc; XBB.1 nLuc; XBB.1.5 nLuc). Amongst the mouse adapted (MA) viruses, a wide range of disease outcomes were observed including mortality, weight loss, lung dysfunction, and tissue viral loads in the lung and nasal turbinates. Intriguingly, XBB.1 MA and XBB.1.5 MA strains, which contained identical mutations throughout except at position F486S/P in S, exhibited divergent disease outcomes in mice (Ao et al., 2023). XBB.1.5 MA infection was associated with significant weight loss and ∼45 % mortality across two independent studies, while XBB.1 MA infected animals suffered from mild weight loss and only 10 % mortality across the same two independent studies. Additionally, the development and use of nanoluciferase expressing strains provided moderate throughput for live virus neutralization assays. The availability of small animal models for the assessment of Omicron VOC disease potential will enable refined capacity to evaluate the efficacy of on market and pre-clinical therapeutics and interventions.

Identifying physiological traits related with drought tolerance and water‐use efficiency in floral hemp (Cannabis sativa L.)

AbstractHemp (Cannabis sativa L.) is a reemerging crop that was once deeply rooted in many global civilizations. Due to climate change and the increasing risk of water‐deficit situations, it is important to use water judiciously. Hemp production has interested many producers; however, due to its past illegal status, there is a lack of research‐based knowledge about the physiological parameters that are affected by drought and which parameters could be responsible for drought tolerance. Therefore, our objective was to study and understand the effects of different drought intensities and timings on physiological parameters such as water‐use efficiency (WUE), photosynthesis, stomatal conductance, and fluorescence parameters and determine if cultivar variation exists as this could mean the possibility of selection for drought‐tolerant cultivars. In addition, we tested if carbon isotope discrimination can be used to predict whole plant WUE as this technique is quick and allows moderate throughput for selection. Hemp cultivars BaOx and Cherry Mom were grown in a greenhouse from July to October during 2021 and 2022 under different water stress intensities and timings. During the water stress period, WUE was determined by the gravimetric method and photosynthetic traits were measured using two portable gas analyzers (LI‐6800). Moderate water stress (30%–50% field capacity) was found to have the least effect on physiological parameters studied, while intense water stresses significantly reduced many physiological parameters such as photosynthesis, stomatal conductance (gs), and electron transport rate (ETR). It was found that the cultivar BaOx had a greater WUE than Cherry Mom. This was confirmed with carbon isotope discrimination measurements, which were demonstrated to estimate WUE accurately, and therefore, this technique could be used for germplasm screening. Drought first decreased gs, which caused the reduction in photosynthesis, although cultivar variation in these traits was not observed. Twenty days after drought, negative effects on fluoresce parameters such as ETR were observed with the cultivar Cherry Mon being more affected. This study states that hemp is negatively affected by different timings and intensities of drought; however, there is physiological variation in the response between cultivars. More research is needed to investigate the sources of genotypic variation in physiological parameters to find the sources of drought tolerance.

Phenotyping and predicting wheat spike characteristics using image analysis and machine learning

AbstractImprovements in trait phenotyping are needed to increase the quantity and quality of data available for genetic improvement of crops. In this study, we used moderate throughput image analysis and machine learning as a pipeline for phenotyping a key wheat spike characteristic: spikelet number per spike. A population of 594 soft red winter wheat inbred lines was evaluated in the field for 2 years and images of wheat spikes were taken and used to train deep‐learning algorithms to predict spikelet number. A total of 12,717 images were used to train, test, and validate a basic regression convolutional neural network (CNN), a visual geometry group application regression model, VGG16, the ResNet152V2 model, and the EfficientNetV2L model. The EfficientNetV2L model was the most accurate, having the lowest mean absolute error, second lowest root mean square error, and highest coefficient of determination (mean absolute error [MAE] = 0.60, root mean square error [RMSE] = 0.79, and R2 = 0.90). The ResNet152V2 model was slightly less accurate with a slightly better fit (MAE = 0.61,m RMSE = 0.78, and R2 = 0.87), followed by the basic CNN (MAE = 0.75, RMSE = 1.00, and R2 = 0.74) and finally by the VGG16 (MAE = 1.51, RMSE = 1.29, and R2 = 0.076). With an average error of just above one half of a spikelet, utilizing image analysis and machine learning counting methods could be used for multiple breeding applications, including direct selection of spikelet number, to provide data to identify quantitative trait loci, or for training whole genome selection models.

Securing AES Designs Against Power Analysis Attacks: A Survey

With the advent of Internet of Things (IoT), the call for hardware security has been seriously demanding due to the risks of side-channel attacks from adversaries. Advanced Encryption Standard (AES) is the de facto security standard for such applications and needs to ensure a low power, low area and moderate throughput design apart from providing high security to these devices. Substitution-box (S-box), being the core component of AES, has always drawn the attention of the cryptographic community. A chronological development of the S-box over a period of 20-years since the inception of AES is presented. This paper provides the first comprehensive review of the state-of-the-art S-box design techniques, identifying current advancements and analysing their impact on gate count, area, maximum frequency of operation, throughput and power. The other goal of the survey is to study the countermeasures designed for AES to protect it against side-channel attacks. In particular, we consider the power analysis attacks, and the countermeasures are investigated in terms of their security metrics and design overheads, such as area, power, and performance. The countermeasures are based on hiding or masking approaches depending on their design principle. Similar to the S-box survey, a chronological development of the countermeasures since the discovery of power analysis attacks in 1999, is presented. Finally, we suggest some open research gaps and possible direction of research in terms of S-box and countermeasure designs.

Metrologically Traceable Quantification of 3 Apolipoprotein E Isoforms in Cerebrospinal Fluid.

APOE genotype is associated with Alzheimer disease. Thus, the concentration of apolipoprotein E (apoE) isoforms in cerebrospinal fluid (CSF) could be altered in dementia. However, conflicting results have been obtained in different studies. Carefully validated and standardized assays could improve the interpretation of research findings, allow their replication in other laboratories, and generalize their application. To evaluate this hypothesis, we aimed to develop, validate, and standardize a new measurement procedure using LC-MS/MS. Purified recombinant apoE protein standards (E2, E3, E4) were thoroughly characterized and used to assign the concentration of a matrix-matched calibration material that contained each apoE isoform, which ensured the metrological traceability of results. The assay of each isoform in human CSF was precise (≤11%CV) and of moderate throughput (approximately 80 samples per day). It demonstrated good linearity and parallelism for lumbar CSF, ventricular CSF, and bovine CSF. The use of an SI-traceable matrix-matched calibrator enabled precise and accurate measurements. There was no association observed between total apoE concentration and the number of Ɛ4 alleles in a cohort of 322 participants. However, the concentration of each isoform was significantly different in heterozygotes, with E4 > E3 > E2. Isoform concentrations were associated with cognitive and motor symptoms but contributed negligibly to a predictive model of cognitive impairment that included established CSF biomarkers. Our method simultaneously measures each apoE isoform in human CSF with excellent precision and accuracy. A secondary matrix-matched material has been developed and is available to other laboratories to improve interlaboratory agreement.

A novel ex vivo assay to define charge-balanced electrical stimulation parameters for neural precursor cell activation in vivo

Endogenous neural stem cells and their progeny (together termed neural precursor cells (NPCs)) are promising candidates to facilitate neuroregeneration. Charge-balanced biphasic monopolar stimulation (BPMP) is a clinically relevant approach that can activate NPCs both in vitro and in vivo. Herein, we established a novel ex vivo stimulation system to optimize the efficacy of BPMP electric field (EF) application in activating endogenous NPCs. Using the ex vivo system, we discerned that cathodal amplitude of 200 μA resulted in the greatest NPC pool expansion and enhanced cathodal migration. Application of the same stimulation parameters in vivo resulted in the same NPC activation in the mouse brain. The design and implementation of the novel ex vivo model bridges the gap between in vitro and in vivo systems, enabling a moderate throughput stimulation system to explore and optimize EF parameters that can be applied to clinically relevant brain injury/disease models.

High-Q Thin-Film Lithium Niobate Microrings Fabricated with Wet Etching.

Thin-film lithium niobate (TFLN) has been widely used in electro-optic modulators, acoustic--optic modulators, electro-optic frequency combs, and nonlinear wavelength converters owing to the excellent optical properties of lithium niobate. The performance of these devices is highly dependent on the fabrication quality of TFLN. Although state-of-the-art TFLN microrings with an intrinsic quality factor (Q-factor) exceeding 1 × 107 have been realized by inductively coupled plasma-reactive ion etching (ICP-RIE) and chemical mechanical polishing (CMP), ICP-RIE has moderate throughput, moderate reproducibility, and high cost in etching TFLN, while CMP features moderate throughput and low cost in etching TFLN. Here, a wet etching method for TFLN, leading to the fabrication of a micro-racetrack with an intrinsic Q-factor of over 9.27 × 106 is developed. The suitability of this method to fabricate a narrow coupling gap between the bus waveguide and microring enables the coupling conditions of the microring to be customized. This method features a high throughput, a high reproducibility, and a low cost in etching TFLN, showing the potential to boost the mass production of integrated LN photonic devices with high fidelity and affordabilitydramatically.

Mechano-Node-Pore Sensing: A Rapid, Label-Free Platform for Multi-Parameter Single-Cell Viscoelastic Measurements.

Cellular mechanical properties are involved in a wide variety of biological processes and diseases, ranging from stem cell differentiation to cancer metastasis. Conventional methods for measuring these properties, such as atomic force microscopy (AFM) and micropipette aspiration (MA), capture rich information, reflecting a cell's full viscoelastic response; however, these methods are limited by very low throughput. High-throughput approaches, such as real-time deformability cytometry (RT-DC), can only measure limited mechanical information, as they are often restricted to single-parameter readouts that only reflect a cell's elastic properties. In contrast to these methods, mechano-node-pore sensing (mechano-NPS) is a flexible, label-free microfluidic platform that bridges the gap in achieving multi-parameter viscoelastic measurements of a cell with moderate throughput. A direct current (DC) measurement is used to monitor cells as they transit a microfluidic channel, tracking their size and velocity before, during, and after they are forced through a narrow constriction. This information (i.e., size and velocity) is used to quantify each cell's transverse deformation, resistance to deformation, and recovery from deformation. In general, this electronics-based microfluidic platform provides multiple viscoelastic cell properties, and thus a more complete picture of a cell's mechanical state. Because it requires minimal sample preparation, utilizes a straightforward electronic measurement (in contrast to a high-speed camera), and takes advantage of standard soft lithography fabrication, the implementation of this platform is simple, accessible, and adaptable to downstream analysis. This platform's flexibility, utility, and sensitivity have provided unique mechanical information on a diverse range of cells, with the potential for many more applications in basic science and clinical diagnostics.

Microfabricated disk technology: Rapid scale up in midbrain organoid generation.

By providing a three-dimensional in vitro culture system with key features of the substantia nigra region in the brain, 3D neuronal organoids derived from human induced pluripotent stem cells (iPSCs) provide living neuronal tissue resembling the midbrain region of the brain. However, a major limitation of conventional brain organoid culture is that it is often labor-intensive, requiring highly specialized personnel for moderate throughput. Additionally, the methods published for long-term cultures require time-consuming maintenance to generate brain organoids in large numbers. With the increasing need for human midbrain organoids (hMOs) to better understand and model Parkinson's disease (PD) in a dish, there is a need to implement new workflows and methods to both generate and maintain hMOs, while minimizing batch to batch variation. In this study, we developed a method with microfabricated disks to scale up the generation of hMOs. This opens up the possibility to generate larger numbers of hMOs, in a manner that minimizes the amount of labor required, while decreasing variability and maintaining the viability of these hMOs over time. Taken together, producing hMOs in this manner opens up the potential for these to be used to further PD studies.

Protease inhibitor Camostat Mesyalte blocks wild type SARS-CoV-2 and D614G viral entry in human engineered miniature lungs

The catastrophic global effects of the SARS-CoV-2 pandemic highlight the need to develop novel therapeutics strategies to prevent and treat viral infections of the respiratory tract. To enable this work, we need scalable, affordable, and physiologically relevant models of the human lung, the primary organ involved in the pathogenesis of COVID-19. To date, most COVID-19 in vitro models rely on platforms such as cell lines and organoids. While 2D and 3D models have provided important insights, human distal lung models that can model epithelial viral uptake have yet to be established. We hypothesized that by leveraging techniques of whole organ engineering and directed differentiation of induced pluripotent stem cells (iPSC) we could model human distal lung epithelium, examine viral infection at the tissue level in real time, and establish a platform for COVID-19 related research ex vivo. In the present study, we used type 2 alveolar epithelial cells (AT2) derived from human iPSCs to repopulate whole rat lung acellular scaffolds and maintained them in extended biomimetic organ culture for 30 days to induce the maturation of distal lung epithelium. We observed emergence of a mixed type 1 and type 2 alveolar epithelial phenotype during tissue formation. When exposing our system to a pseudotyped lentivirus containing the spike of wildtype SARS-CoV-2 and the more virulent D614G, we observed progression of the infection in real time. We then found that the protease inhibitor Camostat Mesyalte significantly reduced viral transfection in distal lung epithelium. In summary, our data show that a mature human distal lung epithelium can serve as a novel moderate throughput research platform to examine viral infection and to evaluate novel therapeutics ex vivo.

Pharmacoresponsiveness of spontaneous recurrent seizures and the comorbid sleep disorder of epileptic Kcna1-null mice

Drug resistant epilepsy affects ∼30% of people with epilepsy and is associated with epilepsy syndromes with frequent and multiple types of seizures, lesions or cytoarchitectural abnormalities, increased risk of mortality and comorbidities such as cognitive impairment and sleep disorders. A limitation of current preclinical models is that spontaneous seizures with comorbidities take time to induce and test, thus making them low-throughput. Kcna1-null mice exhibit all the characteristics of drug resistant epilepsy with spontaneous seizures and comorbidities occurring naturally; thus, we aimed to determine whether they also demonstrate pharmacoresistanct seizures and the impact of medications on their sleep disorder comorbidity. In this exploratory study, Kcna1-null mice were treated with one of four conventional antiseizure medications, carbamazepine, levetiracetam, phenytoin, and phenobarbital using a moderate throughput protocol (vehicle for 2 days followed by 2 days of treatment with high therapeutic doses selected based on published data in the 6 Hz model of pharmacoresistant seizures). Spontaneous recurrent seizures and vigilance states were recorded with video-EEG/EMG. Carbamazepine, levetiracetam and phenytoin had partial efficacy (67%, 75% and 33% were seizure free, respectively), whereas phenobarbital was fully efficacious and conferred seizure freedom to all mice. Thus, seizures of Kcna1-null mice appear to be resistant to three of the drugs tested. Levetiracetam failed to affect sleep architecture, carbamazepine and phenytoin had moderate effects, and phenobarbital, as predicted, restored sleep architecture. Data suggest Kcna1-null mice may be a moderate throughput model of drug resistant epilepsy useful in determining mechanisms of pharmacoresistance and testing novel therapeutic strategies.

Grant-Free Access via Bilinear Inference for Cell-Free MIMO With Low-Coherence Pilots

We propose a novel joint activity, channel and data estimation (JACDE) scheme for multiple-input multiple-output (MIMO) systems. The contribution aims to allow significant overhead reduction of MIMO systems by enabling grant-free access, while maintaining moderate throughput per user. To that end, we extend the conventional MIMO transmission framework so as to incorporate activity detection capability without resorting to spreading informative data symbols, in contrast with related work which typically relies on signal spreading. Our method leverages a Bayesian message passing scheme based on Gaussian approximation, which jointly performs active user detection (AUD), channel estimation (CE), and multi-user detection (MUD), incorporating also a well-structured low-coherence pilot design based on frame theory, which mitigates pilot contamination, and finally complemented with a detector empowered by bilinear message passing. The efficacy of the resulting JACDE-based grant-free access scheme in the cell-free MIMO system setup compliant with fifth generation (5G) new radio (NR) orthogonal frequency-division multiplexing (OFDM) signaling is demonstrated by simulation results. The results are shown to outperform the current state-of-the-art and approach the performance of an idealized (genie-aided) scheme in which user activity and channel coefficients are perfectly known.

Viability-Resolved Metagenomics Reveals Antagonistic Colonization Dynamics of Staphylococcus epidermidis Strains on Preterm Infant Skin.

ABSTRACTPreterm infants are at increased risk of infections caused by coagulase-negative staphylococci (CoNS) that colonize skin. Technical barriers in sequencing low-microbial-biomass skin swabs from preterm infants hinder attempts to gain a strain-level understanding of CoNS colonization dynamics within their developing skin microbiome. Here, the microbiome of five skin sites and available stool was studied from four preterm infants hospitalized over their first 2 months of life. We used propidium monoazide treatment of samples to enrich for the viable microbiome and metagenomic shotgun sequencing to resolve species and strains. The microbiome of different skin sites overlapped with each other, was dominated by the CoNS species Staphylococcus epidermidis and Staphylococcus capitis, and was distinct from stool. Species diversity on skin increased over time despite antibiotic exposure. Evidence of antagonism between the most common S. epidermidis strains, ST2 and ST59, included negative relationships for species correlation networks and in situ replication rates and that ST2 colonized skin earlier but was often replaced by ST59 over time. Experiments done with reference isolates showed that ST2 produced more biofilm than ST59 on plastic surfaces, which was reduced in mixed culture. We also discovered that a rare S. epidermidis strain, ST5, grew rapidly in stool in association with Stenotrophomonas maltophilia from a suspected episode of infection. Viability treatment of samples and moderate throughput shotgun sequencing provides strain-level information about CoNS colonization dynamics of preterm infant skin that ultimately might be exploited to prevent infections.IMPORTANCE The skin is a habitat for microbes that commonly infect preterm infants, but the use of sequencing for fine-scale study of the microbial communities of skin that develop in these infants has been limited by technical barriers. We treated skin swabs of preterm infants with a photoreactive dye that eliminates DNA from nonviable microbes and then sequenced the remaining DNA. We found that two strains of the most common species, Staphylococcus epidermidis, showed an antagonistic relationship on skin by cooccurring with different species, replicating fastest in different samples, and dominating skin sites at different times. Representatives of these strains also differed in their ability to stick to plastic surfaces—an important pathogenicity trait of this species. Our study shows the feasibility of gaining detailed information about strain colonization dynamics from this difficult-to-sequence body site of preterm infants, which might be used to guide novel approaches to prevent infections.

Characterization of data compression across CPU platforms and accelerators

AbstractThe ever increasing amount of generated data makes it more and more beneficial to utilize compression to trade computations for data movement and reduced storage requirements. Lately, dedicated accelerators have been introduced to offload compression tasks from the main processor. However, research is lacking when it comes to the system costs for incorporating compression. This is especially true for the influence of the CPU platform and accelerators on the compression. This work will show that for general‐purpose lossless compression algorithms following can be recommended: (1) snappy for high throughput, but low compression ratio; (2) zstandard level 2 for moderate throughput and compression ratio; (3) xz level 5 for low throughput, but high compression ratio. And it will show that the selected platforms (ARM, IBM or Intel) have no influence on the algorithm's performance. Furthermore, it will show that the accelerator's zlib implementation achieves a comparable compression ratio as zlib level 2 on a CPU, while having up to the throughput and utilizing over 80% less CPU resources. This suggests that the overhead of offloading compression is limited but present. Overall, this work will allow system designers to identify deployment opportunities for compression while considering integration constraints.

Single Cell Technologies: Beyond Microfluidics.

Single-cell RNA-sequencing (scRNA-seq) has been widely adopted in recent years due to standardized protocols and automation, reliability, and standardized bioinformatic pipelines. The most widely adopted platform is the 10× Genomics solution. Although powerful, this system is limited by its high cost, moderate throughput, and the inability to customize due to fixed kit components. This study will cover new approaches that do not rely on microfluidics and thus have low entry costs, are highly customizable, and are within the reach of any laboratory possessing molecular biology expertise.